Impact of the Economic Structure of Cities on Urban Scaling Factors

Implications for Urban Material and Energy Flows in China

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8 Citations (Scopus)

Abstract

We explore the population-scaling and gross domestic product (GDP)-scaling relationships of material and energy flow (MEF) parameters in different city types based on economic structure. Using migration-corrected population data, we classify 233 Chinese city propers (Shiqu) as “highly industrial” (share of secondary GDP exceeds 63.9%), “highly commercial” (share of tertiary GDP exceeds 52.6%), and “mixed-economy” (the remaining cities). We find that, first, the GDP population-scaling factors differ in the different city types. Highly commercial and mixed-economy cities exhibit superlinear GDP population-scaling factors greater than 1, whereas highly industrial cities are sublinear. Second, GDP scaling better correlates with city-wide MEF parameters in Chinese cities; these scaling relationships also show differences by city typology. Third, highly commercial cities are significantly different from others in demonstrating greater average per capita household income creation relative to per capita GDP. Further, highly industrial cities show an apparent cap in population. This also translates to lower densities in highly industrial cities compared to other types, showing a size effect on urban population density. Finally, a multiple variable regression of total household electricity showed significant and positive correlation with population, income effect, and urban form effect. With such multivariate modeling, the apparent superlinearity of household electricity use with respect to population is no longer observed. Our study enhances understanding of MEFs associated with Chinese cities and provides new insights into the patterns of scaling observed in different city types by economic structure. Results recommend dual scaling by GDP and by population for MEF parameters and suggest caution in applying universal scaling factors to all cities in a country.

Original languageEnglish (US)
Pages (from-to)392-405
Number of pages14
JournalJournal of Industrial Ecology
Volume22
Issue number2
DOIs
StatePublished - Apr 1 2018

Fingerprint

economic structure
energy flow
gross domestic product
scaling
energy
China
Gross Domestic Product
electricity
city
material flow
income effect
population migration
economy
urban population
population density
household income
typology
size effect
regression
multiple regression

Keywords

  • China
  • city typology
  • economic structure
  • material and energy flows
  • population and GDP
  • scaling factors

Cite this

@article{de9eb4d41d7e40e7b8a792aeb6c7ac16,
title = "Impact of the Economic Structure of Cities on Urban Scaling Factors: Implications for Urban Material and Energy Flows in China",
abstract = "We explore the population-scaling and gross domestic product (GDP)-scaling relationships of material and energy flow (MEF) parameters in different city types based on economic structure. Using migration-corrected population data, we classify 233 Chinese city propers (Shiqu) as “highly industrial” (share of secondary GDP exceeds 63.9{\%}), “highly commercial” (share of tertiary GDP exceeds 52.6{\%}), and “mixed-economy” (the remaining cities). We find that, first, the GDP population-scaling factors differ in the different city types. Highly commercial and mixed-economy cities exhibit superlinear GDP population-scaling factors greater than 1, whereas highly industrial cities are sublinear. Second, GDP scaling better correlates with city-wide MEF parameters in Chinese cities; these scaling relationships also show differences by city typology. Third, highly commercial cities are significantly different from others in demonstrating greater average per capita household income creation relative to per capita GDP. Further, highly industrial cities show an apparent cap in population. This also translates to lower densities in highly industrial cities compared to other types, showing a size effect on urban population density. Finally, a multiple variable regression of total household electricity showed significant and positive correlation with population, income effect, and urban form effect. With such multivariate modeling, the apparent superlinearity of household electricity use with respect to population is no longer observed. Our study enhances understanding of MEFs associated with Chinese cities and provides new insights into the patterns of scaling observed in different city types by economic structure. Results recommend dual scaling by GDP and by population for MEF parameters and suggest caution in applying universal scaling factors to all cities in a country.",
keywords = "China, city typology, economic structure, material and energy flows, population and GDP, scaling factors",
author = "Anu Ramaswami and Daqian Jiang and Kangkang Tong and Zhao, {Zhirong J}",
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TY - JOUR

T1 - Impact of the Economic Structure of Cities on Urban Scaling Factors

T2 - Implications for Urban Material and Energy Flows in China

AU - Ramaswami, Anu

AU - Jiang, Daqian

AU - Tong, Kangkang

AU - Zhao, Zhirong J

PY - 2018/4/1

Y1 - 2018/4/1

N2 - We explore the population-scaling and gross domestic product (GDP)-scaling relationships of material and energy flow (MEF) parameters in different city types based on economic structure. Using migration-corrected population data, we classify 233 Chinese city propers (Shiqu) as “highly industrial” (share of secondary GDP exceeds 63.9%), “highly commercial” (share of tertiary GDP exceeds 52.6%), and “mixed-economy” (the remaining cities). We find that, first, the GDP population-scaling factors differ in the different city types. Highly commercial and mixed-economy cities exhibit superlinear GDP population-scaling factors greater than 1, whereas highly industrial cities are sublinear. Second, GDP scaling better correlates with city-wide MEF parameters in Chinese cities; these scaling relationships also show differences by city typology. Third, highly commercial cities are significantly different from others in demonstrating greater average per capita household income creation relative to per capita GDP. Further, highly industrial cities show an apparent cap in population. This also translates to lower densities in highly industrial cities compared to other types, showing a size effect on urban population density. Finally, a multiple variable regression of total household electricity showed significant and positive correlation with population, income effect, and urban form effect. With such multivariate modeling, the apparent superlinearity of household electricity use with respect to population is no longer observed. Our study enhances understanding of MEFs associated with Chinese cities and provides new insights into the patterns of scaling observed in different city types by economic structure. Results recommend dual scaling by GDP and by population for MEF parameters and suggest caution in applying universal scaling factors to all cities in a country.

AB - We explore the population-scaling and gross domestic product (GDP)-scaling relationships of material and energy flow (MEF) parameters in different city types based on economic structure. Using migration-corrected population data, we classify 233 Chinese city propers (Shiqu) as “highly industrial” (share of secondary GDP exceeds 63.9%), “highly commercial” (share of tertiary GDP exceeds 52.6%), and “mixed-economy” (the remaining cities). We find that, first, the GDP population-scaling factors differ in the different city types. Highly commercial and mixed-economy cities exhibit superlinear GDP population-scaling factors greater than 1, whereas highly industrial cities are sublinear. Second, GDP scaling better correlates with city-wide MEF parameters in Chinese cities; these scaling relationships also show differences by city typology. Third, highly commercial cities are significantly different from others in demonstrating greater average per capita household income creation relative to per capita GDP. Further, highly industrial cities show an apparent cap in population. This also translates to lower densities in highly industrial cities compared to other types, showing a size effect on urban population density. Finally, a multiple variable regression of total household electricity showed significant and positive correlation with population, income effect, and urban form effect. With such multivariate modeling, the apparent superlinearity of household electricity use with respect to population is no longer observed. Our study enhances understanding of MEFs associated with Chinese cities and provides new insights into the patterns of scaling observed in different city types by economic structure. Results recommend dual scaling by GDP and by population for MEF parameters and suggest caution in applying universal scaling factors to all cities in a country.

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KW - economic structure

KW - material and energy flows

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